Tracking algorithm with radar and infrared sensors using a novel adaptive grid interacting multiple model

Abstract

This study presents a novel adaptive grid interacting multiple model based on modified iterated extended Kalman filter (AGIMM‐MIEKF) for tracking a manoeuvreing target using radar/infrared (IR) heterogeneous sensors. This tracking algorithm is developed by aligning observation data of radar/IR sensors in time, and fusing the synthesised data before applying to AGIMM‐MIEKF algorithm. Under the architecture of the proposed algorithm, the AGIMM deals with the model switching, whereas the MIEKF accounts for non‐linearity in the dynamic system models. A new measurement update equation and an iterated termination criterion are derived and applied to radar/IR tracking system. The simulation results show that the presented AGIMM‐MIEKF has higher tracking precision than the traditional algorithms.